Substantial effort and attention continues toward the development of newer and more sustainable energy supplies, the conservation of energy by increased energy efficiency remains crucial to the world's energy future. According to an October 2010 report from the U.S. Department of Energy, heating and cooling account for 56% of the energy use in a typical U.S. home, making it the largest energy expense for most homes. Along with improvements in the physical plant associated with home heating and cooling (e.g., improved insulation, higher efficiency furnaces), substantial increases in energy efficiency can be achieved by better control and regulation of home heating and cooling equipment. By activating heating, ventilation, and air conditioning (HVAC) equipment for judiciously selected time intervals and carefully chosen operating levels, substantial energy can be saved while at the same time keeping the living space suitably comfortable for its occupants.
For the purposes of controlling one or more HVAC systems for climate control in an enclosure, systems for that incorporate a distributed array of wirelessly communicating sensing units are known in art and discussed, for example, in U.S. Pat. No. 5,395,042, which is incorporated by reference herein. Different methods for powering the wirelessly communicating sensing units are also known in the art, including using standard building AC outlet power as discussed in US20080015740A1, standard battery-only power as discussed in US20070114295A1, and solar-charged battery power as discussed U.S. Pat. No. 5,395,042, supra. For wirelessly communicating thermostatic sensing units having control wires running directly to a conventional HVAC system, so-called “power stealing” or “parasitic powering” methods such as those discussed in U.S. Pat. No. 7,510,126 can be used, wherein a relatively small amount of power is extracted from a call relay coil voltage provided by the HVAC system. Each of the above-cited patents and patent publications is incorporated by reference herein.
For the purposes of controlling one or more HVAC systems for climate control in an enclosure, various computational methods have been proposed for optimizing the control of one or more HVAC systems in a manner that accommodates a balance of human comfort and energy efficiency, the optimizing being based at least in part on current and historical environmental readings and inputs acquired at a distributed network of sensing nodes. Examples of such proposals are discussed in U.S. Pat. No. 7,847,681 B2 and US20100262298A1, each of which is incorporated by reference herein. Generally speaking, such computational methods can involve multidimensional feedback control system characterization or “learning” of a climate control environment having one or more HVAC systems and/or simultaneous optimization of plural multidimensional feedback control system performance metrics (such as a “total suffering” metric described in US20100262298A1, supra) based on learned or known multidimensional feedback control system parameters and constraints characteristic of the climate control environment. Such computational tasks, which are termed “characterization and/or optimization algorithms” hereinbelow for clarity of description and not by way of limitation, can be of relatively high computational complexity and therefore can represent a relatively high computational load.
Provided according to an embodiment is a climate control system comprising a plurality of wirelessly communicating sensing microsystems, each sensing microsystem including a temperature sensor and a processor, at least one of the sensing microsystems being coupled to an HVAC unit for control thereof. The plurality of sensing microsystems is configured to jointly carry out at least one shared computational task associated with the control of the HVAC unit. Each sensing microsystem includes a power management circuit configured to determine an amount of electrical power available for dedication to the at least one shared computational task. The at least one shared computational task is apportioned among respective ones of the plurality of sensing microsystems according to the amount of electrical power determined to be available for dedication thereto at each respective sensing microsystem.